Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells10
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory566.4 KiB
Average record size in memory58.0 B

Variable types

Text3
Categorical1
Numeric2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15819/S/1/datasetView.do

Alerts

금액 is highly skewed (γ1 = 21.48247464)Skewed

Reproduction

Analysis started2024-05-11 02:38:38.573387
Analysis finished2024-05-11 02:38:42.915284
Duration4.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2066
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:38:43.385051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.1855
Min length2

Characters and Unicode

Total characters71855
Distinct characters429
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)1.7%

Sample

1st row신정동일하이빌
2nd row한신1
3rd rowDMC센트레빌
4th row상도sh-ville
5th row수색대림한숲타운
ValueCountFrequency (%)
아파트 88
 
0.8%
래미안 34
 
0.3%
목동7단지 22
 
0.2%
신내 22
 
0.2%
잠실리센츠 19
 
0.2%
잠실엘스 18
 
0.2%
신림현대 18
 
0.2%
힐스테이트 18
 
0.2%
마포래미안푸르지오 18
 
0.2%
길음뉴타운푸르지오아파트2,3단지 18
 
0.2%
Other values (2120) 10257
97.4%
2024-05-11T02:38:44.727535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2189
 
3.0%
파 2132
 
3.0%
지 2030
 
2.8%
트 1976
 
2.7%
대 1837
 
2.6%
단 1625
 
2.3%
동 1525
 
2.1%
차 1468
 
2.0%
신 1462
 
2.0%
성 1264
 
1.8%
Other values (419) 54347
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65675
91.4%
Decimal Number 4001
 
5.6%
Uppercase Letter 679
 
0.9%
Space Separator 592
 
0.8%
Lowercase Letter 270
 
0.4%
Open Punctuation 166
 
0.2%
Close Punctuation 166
 
0.2%
Other Punctuation 155
 
0.2%
Dash Punctuation 136
 
0.2%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2189
 
3.3%
파 2132
 
3.2%
지 2030
 
3.1%
트 1976
 
3.0%
대 1837
 
2.8%
단 1625
 
2.5%
동 1525
 
2.3%
차 1468
 
2.2%
신 1462
 
2.2%
성 1264
 
1.9%
Other values (373) 48167
73.3%
Uppercase Letter
ValueCountFrequency (%)
S 131
19.3%
K 109
16.1%
C 64
9.4%
H 42
 
6.2%
L 42
 
6.2%
M 42
 
6.2%
D 42
 
6.2%
I 40
 
5.9%
E 38
 
5.6%
A 35
 
5.2%
Other values (7) 94
13.8%
Lowercase Letter
ValueCountFrequency (%)
e 165
61.1%
l 32
 
11.9%
i 22
 
8.1%
v 17
 
6.3%
s 10
 
3.7%
h 9
 
3.3%
c 4
 
1.5%
w 4
 
1.5%
k 3
 
1.1%
a 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 1221
30.5%
2 1113
27.8%
3 492
12.3%
4 284
 
7.1%
5 251
 
6.3%
6 193
 
4.8%
7 145
 
3.6%
8 119
 
3.0%
9 101
 
2.5%
0 82
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 133
85.8%
. 22
 
14.2%
Space Separator
ValueCountFrequency (%)
592
100.0%
Open Punctuation
ValueCountFrequency (%)
( 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65675
91.4%
Common 5224
 
7.3%
Latin 956
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2189
 
3.3%
파 2132
 
3.2%
지 2030
 
3.1%
트 1976
 
3.0%
대 1837
 
2.8%
단 1625
 
2.5%
동 1525
 
2.3%
차 1468
 
2.2%
신 1462
 
2.2%
성 1264
 
1.9%
Other values (373) 48167
73.3%
Latin
ValueCountFrequency (%)
e 165
17.3%
S 131
13.7%
K 109
11.4%
C 64
 
6.7%
H 42
 
4.4%
L 42
 
4.4%
M 42
 
4.4%
D 42
 
4.4%
I 40
 
4.2%
E 38
 
4.0%
Other values (19) 241
25.2%
Common
ValueCountFrequency (%)
1 1221
23.4%
2 1113
21.3%
592
11.3%
3 492
9.4%
4 284
 
5.4%
5 251
 
4.8%
6 193
 
3.7%
( 166
 
3.2%
) 166
 
3.2%
7 145
 
2.8%
Other values (7) 601
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65675
91.4%
ASCII 6173
 
8.6%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2189
 
3.3%
파 2132
 
3.2%
지 2030
 
3.1%
트 1976
 
3.0%
대 1837
 
2.8%
단 1625
 
2.5%
동 1525
 
2.3%
차 1468
 
2.2%
신 1462
 
2.2%
성 1264
 
1.9%
Other values (373) 48167
73.3%
ASCII
ValueCountFrequency (%)
1 1221
19.8%
2 1113
18.0%
592
 
9.6%
3 492
 
8.0%
4 284
 
4.6%
5 251
 
4.1%
6 193
 
3.1%
( 166
 
2.7%
) 166
 
2.7%
e 165
 
2.7%
Other values (35) 1530
24.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2071
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:38:45.996890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)1.7%

Sample

1st rowA15807315
2nd rowA13993503
3rd rowA12072801
4th rowA15603004
5th rowA12287204
ValueCountFrequency (%)
a15805115 22
 
0.2%
a13822003 19
 
0.2%
a12175203 18
 
0.2%
a13611007 18
 
0.2%
a15101508 18
 
0.2%
a13822004 18
 
0.2%
a13509010 17
 
0.2%
a10026988 17
 
0.2%
a14272314 16
 
0.2%
a15685206 15
 
0.1%
Other values (2061) 9822
98.2%
2024-05-11T02:38:47.498514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18403
20.4%
1 17409
19.3%
A 9992
11.1%
3 8962
10.0%
2 7964
8.8%
5 6241
 
6.9%
8 5729
 
6.4%
7 4963
 
5.5%
4 3877
 
4.3%
6 3391
 
3.8%
Other values (2) 3069
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
88.9%
Uppercase Letter 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18403
23.0%
1 17409
21.8%
3 8962
11.2%
2 7964
10.0%
5 6241
 
7.8%
8 5729
 
7.2%
7 4963
 
6.2%
4 3877
 
4.8%
6 3391
 
4.2%
9 3061
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9992
99.9%
B 8
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 80000
88.9%
Latin 10000
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18403
23.0%
1 17409
21.8%
3 8962
11.2%
2 7964
10.0%
5 6241
 
7.8%
8 5729
 
7.2%
7 4963
 
6.2%
4 3877
 
4.8%
6 3391
 
4.2%
9 3061
 
3.8%
Latin
ValueCountFrequency (%)
A 9992
99.9%
B 8
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18403
20.4%
1 17409
19.3%
A 9992
11.1%
3 8962
10.0%
2 7964
8.8%
5 6241
 
6.9%
8 5729
 
6.4%
7 4963
 
5.5%
4 3877
 
4.3%
6 3391
 
3.8%
Other values (2) 3069
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3760 
광고료수익
1077 
잡수익
1051 
승강기수익
840 
주차장수익
781 
Other values (10)
2491 

Length

Max length9
Median length5
Mean length5.0096
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타운영수익
2nd row광고료수익
3rd row광고료수익
4th row주차장수익
5th row임대료수익

Common Values

ValueCountFrequency (%)
연체료수익 3760
37.6%
광고료수익 1077
 
10.8%
잡수익 1051
 
10.5%
승강기수익 840
 
8.4%
주차장수익 781
 
7.8%
기타운영수익 738
 
7.4%
고용안정사업수익 443
 
4.4%
검침수익 249
 
2.5%
임대료수익 238
 
2.4%
알뜰시장수익 203
 
2.0%
Other values (5) 620
 
6.2%

Length

2024-05-11T02:38:48.210021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3760
37.6%
광고료수익 1077
 
10.8%
잡수익 1051
 
10.5%
승강기수익 840
 
8.4%
주차장수익 781
 
7.8%
기타운영수익 738
 
7.4%
고용안정사업수익 443
 
4.4%
검침수익 249
 
2.5%
임대료수익 238
 
2.4%
알뜰시장수익 203
 
2.0%
Other values (5) 620
 
6.2%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190717
Minimum20190701
Maximum20190731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:38:48.772753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190701
5-th percentile20190701
Q120190708
median20190717
Q320190725
95-th percentile20190731
Maximum20190731
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.9553061
Coefficient of variation (CV)4.9306352 × 10-7
Kurtosis-1.3056474
Mean20190717
Median Absolute Deviation (MAD)9
Skewness-0.14324991
Sum2.0190717 × 1011
Variance99.108119
MonotonicityNot monotonic
2024-05-11T02:38:49.871110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20190731 945
 
9.4%
20190701 636
 
6.4%
20190725 556
 
5.6%
20190715 491
 
4.9%
20190730 485
 
4.9%
20190729 425
 
4.2%
20190717 419
 
4.2%
20190710 401
 
4.0%
20190702 397
 
4.0%
20190722 389
 
3.9%
Other values (21) 4856
48.6%
ValueCountFrequency (%)
20190701 636
6.4%
20190702 397
4.0%
20190703 350
3.5%
20190704 307
3.1%
20190705 356
3.6%
20190706 77
 
0.8%
20190707 56
 
0.6%
20190708 341
3.4%
20190709 284
2.8%
20190710 401
4.0%
ValueCountFrequency (%)
20190731 945
9.4%
20190730 485
4.9%
20190729 425
4.2%
20190728 140
 
1.4%
20190727 122
 
1.2%
20190726 368
 
3.7%
20190725 556
5.6%
20190724 374
 
3.7%
20190723 346
 
3.5%
20190722 389
3.9%

금액
Real number (ℝ)

SKEWED 

Distinct3345
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean274558.49
Minimum-4080000
Maximum60313414
Zeros15
Zeros (%)0.1%
Negative40
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:38:50.457847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4080000
5-th percentile140
Q13220
median30000
Q3100000
95-th percentile1080250
Maximum60313414
Range64393414
Interquartile range (IQR)96780

Descriptive statistics

Standard deviation1631529.7
Coefficient of variation (CV)5.9423756
Kurtosis618.9972
Mean274558.49
Median Absolute Deviation (MAD)28995
Skewness21.482475
Sum2.7455849 × 109
Variance2.6618891 × 1012
MonotonicityNot monotonic
2024-05-11T02:38:51.057368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 698
 
7.0%
50000 568
 
5.7%
100000 444
 
4.4%
70000 149
 
1.5%
60000 140
 
1.4%
20000 135
 
1.4%
80000 121
 
1.2%
150000 115
 
1.1%
40000 115
 
1.1%
200000 98
 
1.0%
Other values (3335) 7417
74.2%
ValueCountFrequency (%)
-4080000 1
< 0.1%
-3764450 1
< 0.1%
-2540000 1
< 0.1%
-1900000 1
< 0.1%
-1553810 1
< 0.1%
-1056000 1
< 0.1%
-556130 1
< 0.1%
-519350 1
< 0.1%
-448000 1
< 0.1%
-369600 1
< 0.1%
ValueCountFrequency (%)
60313414 1
< 0.1%
60000000 1
< 0.1%
50000000 1
< 0.1%
43578820 1
< 0.1%
40500000 1
< 0.1%
37052000 1
< 0.1%
35000000 1
< 0.1%
30026200 1
< 0.1%
28000000 1
< 0.1%
25200000 1
< 0.1%

내용
Text

Distinct5644
Distinct (%)56.5%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:38:51.705904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length64
Mean length13.677878
Min length2

Characters and Unicode

Total characters136642
Distinct characters726
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5408 ?
Unique (%)54.1%

Sample

1st row6월 커피자판기 수익
2nd row금매입(47)
3rd row게시판 광고(조명희-방충망-54)
4th row외부차량 주차비 입금(이종성)
5th row헬스장 임대료(7월)
ValueCountFrequency (%)
관리비 3887
 
15.0%
수납 3765
 
14.5%
연체료 3765
 
14.5%
7월분 332
 
1.3%
6월분 282
 
1.1%
승강기 247
 
1.0%
223
 
0.9%
7월 195
 
0.8%
게시판 194
 
0.7%
입금 186
 
0.7%
Other values (7159) 12890
49.6%
2024-05-11T02:38:53.195972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16073
 
11.8%
료 5596
 
4.1%
수 5165
 
3.8%
리 4993
 
3.7%
비 4728
 
3.5%
0 4122
 
3.0%
1 4108
 
3.0%
관 4102
 
3.0%
체 3936
 
2.9%
납 3886
 
2.8%
Other values (716) 79933
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89438
65.5%
Decimal Number 19145
 
14.0%
Space Separator 16073
 
11.8%
Open Punctuation 3033
 
2.2%
Close Punctuation 3027
 
2.2%
Other Punctuation 2565
 
1.9%
Dash Punctuation 2102
 
1.5%
Uppercase Letter 739
 
0.5%
Math Symbol 299
 
0.2%
Lowercase Letter 160
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5596
 
6.3%
수 5165
 
5.8%
리 4993
 
5.6%
비 4728
 
5.3%
관 4102
 
4.6%
체 3936
 
4.4%
납 3886
 
4.3%
연 3828
 
4.3%
월 1826
 
2.0%
금 1563
 
1.7%
Other values (633) 49815
55.7%
Uppercase Letter
ValueCountFrequency (%)
N 93
12.6%
O 72
 
9.7%
T 54
 
7.3%
G 51
 
6.9%
L 48
 
6.5%
K 46
 
6.2%
B 42
 
5.7%
A 41
 
5.5%
S 39
 
5.3%
D 32
 
4.3%
Other values (14) 221
29.9%
Lowercase Letter
ValueCountFrequency (%)
o 55
34.4%
n 27
16.9%
x 11
 
6.9%
k 11
 
6.9%
s 8
 
5.0%
e 7
 
4.4%
g 6
 
3.8%
b 6
 
3.8%
a 4
 
2.5%
t 4
 
2.5%
Other values (10) 21
 
13.1%
Other Punctuation
ValueCountFrequency (%)
/ 746
29.1%
, 685
26.7%
. 682
26.6%
: 215
 
8.4%
* 117
 
4.6%
@ 45
 
1.8%
% 21
 
0.8%
? 19
 
0.7%
' 11
 
0.4%
# 10
 
0.4%
Other values (4) 14
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 4122
21.5%
1 4108
21.5%
2 2319
12.1%
7 1942
10.1%
6 1524
 
8.0%
3 1295
 
6.8%
4 1075
 
5.6%
5 1045
 
5.5%
9 924
 
4.8%
8 791
 
4.1%
Math Symbol
ValueCountFrequency (%)
~ 253
84.6%
+ 15
 
5.0%
> 11
 
3.7%
= 8
 
2.7%
× 6
 
2.0%
< 5
 
1.7%
→ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2967
98.0%
] 59
 
1.9%
} 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2971
98.0%
[ 62
 
2.0%
Space Separator
ValueCountFrequency (%)
16073
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2102
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89435
65.5%
Common 46305
33.9%
Latin 899
 
0.7%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5596
 
6.3%
수 5165
 
5.8%
리 4993
 
5.6%
비 4728
 
5.3%
관 4102
 
4.6%
체 3936
 
4.4%
납 3886
 
4.3%
연 3828
 
4.3%
월 1826
 
2.0%
금 1563
 
1.7%
Other values (630) 49812
55.7%
Latin
ValueCountFrequency (%)
N 93
 
10.3%
O 72
 
8.0%
o 55
 
6.1%
T 54
 
6.0%
G 51
 
5.7%
L 48
 
5.3%
K 46
 
5.1%
B 42
 
4.7%
A 41
 
4.6%
S 39
 
4.3%
Other values (34) 358
39.8%
Common
ValueCountFrequency (%)
16073
34.7%
0 4122
 
8.9%
1 4108
 
8.9%
( 2971
 
6.4%
) 2967
 
6.4%
2 2319
 
5.0%
- 2102
 
4.5%
7 1942
 
4.2%
6 1524
 
3.3%
3 1295
 
2.8%
Other values (29) 6882
14.9%
Han
ValueCountFrequency (%)
人 1
33.3%
日 1
33.3%
孝 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89435
65.5%
ASCII 47196
34.5%
None 7
 
< 0.1%
CJK 3
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16073
34.1%
0 4122
 
8.7%
1 4108
 
8.7%
( 2971
 
6.3%
) 2967
 
6.3%
2 2319
 
4.9%
- 2102
 
4.5%
7 1942
 
4.1%
6 1524
 
3.2%
3 1295
 
2.7%
Other values (70) 7773
16.5%
Hangul
ValueCountFrequency (%)
료 5596
 
6.3%
수 5165
 
5.8%
리 4993
 
5.6%
비 4728
 
5.3%
관 4102
 
4.6%
체 3936
 
4.4%
납 3886
 
4.3%
연 3828
 
4.3%
월 1826
 
2.0%
금 1563
 
1.7%
Other values (630) 49812
55.7%
None
ValueCountFrequency (%)
× 6
85.7%
· 1
 
14.3%
CJK
ValueCountFrequency (%)
人 1
33.3%
日 1
33.3%
孝 1
33.3%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

Interactions

2024-05-11T02:38:41.548347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:38:40.856905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:38:41.993529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:38:41.194857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:38:53.546335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3910.268
년월일0.3911.0000.113
금액0.2680.1131.000
2024-05-11T02:38:53.825716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0020.155
금액0.0021.0000.103
비용명0.1550.1031.000

Missing values

2024-05-11T02:38:42.404788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:38:42.731188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

아파트명아파트코드비용명년월일금액내용
61972신정동일하이빌A15807315기타운영수익201907254908296월 커피자판기 수익
42613한신1A13993503광고료수익20190701390000금매입(47)
7695DMC센트레빌A12072801광고료수익2019073150000게시판 광고(조명희-방충망-54)
55504상도sh-villeA15603004주차장수익20190703120000외부차량 주차비 입금(이종성)
12394수색대림한숲타운A12287204임대료수익20190731454545헬스장 임대료(7월)
42367하계극동건영벽산A13987306연체료수익201907257650관리비 연체료 수납
36814거여현대1차A13881603연체료수익201907234400관리비 연체료 수납
15138신내우디안1단지A13113008연체료수익201907231170관리비 연체료 수납
64177은평뉴타운구파발9-2단지A41279920주차장수익201907319113007월 주차비
51900개봉한마을A15209002연체료수익2019072870관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
7493충정리시온A12070201연체료수익20190730750관리비 연체료 수납
10098상암월드컵파크10단지A12179508연체료수익201907308730관리비 연체료 수납
41098월계시영고층A13984005고용안정사업수익201907313480000일자리안정자금수익 차감(미화원)19.02월분
16144묵동브라운스톤태릉A13185508이자수익20190726897023하나(관리비정기예금만기 이자수익)
22504프라이어팰리스A13405003기타운영수익2019070510000마스터카드[풀무원]
27837역삼푸르지오A13592604승강기수익2019072580000107동 202호 승강기사용료 : 전입 7/28
37364월계동현대A13905105잡수익2019071955000세무대행수수료 세액환급
54004신도림대림7차e-편한세상A15288807광고료수익20190711100000우편함광고-현대백화점
54528독산주공14단지A15375809이자수익201907094419445장충만기해지이자(우리1020-332-321011)
27829역삼푸르지오A13592604주차장수익201907239091주차비 6건